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https://api.github.com/repos/huggingface/transformers/issues/5320 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5320/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5320/comments | https://api.github.com/repos/huggingface/transformers/issues/5320/events | https://github.com/huggingface/transformers/issues/5320 | 646,441,144 | MDU6SXNzdWU2NDY0NDExNDQ= | 5,320 | Reformer model axial.position.shape config not working | {
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"Either my calculator and me are wrong or the max pos embedding is not matching the axial pos shape\n\n",
"> Either my calculator and me are wrong or the m... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5319?src=pr&el=h1) Report\n> Merging [#5319](https://codecov.io/gh/huggingface/transformers/pull/5319?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bf0d12c220cfd19025736c488bdabda9efd20b9e&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | When using a `pipeline` for text gerenation with XLNet and transformer-XL, the pipeline adds a long prompt at the beginning to help the model. It messes up with `min_length` and `max_length` so I fixed that by adding to those kwargs (if passed) the length of the prompt.
Also made the prompt use the tokenizer eos tok... | {
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https://api.github.com/repos/huggingface/transformers/issues/5317 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5317/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5317/comments | https://api.github.com/repos/huggingface/transformers/issues/5317/events | https://github.com/huggingface/transformers/pull/5317 | 646,391,778 | MDExOlB1bGxSZXF1ZXN0NDQwNjkwMTYy | 5,317 | Clearer lr schedule math | {
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"looks neat",
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5316?src=pr&el=h1) Report\n> Merging [#5316](https://codecov.io/gh/huggingface/transformers/pull/5316?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/79a82cc06aaa68088639bf9bb000752cfd33a8c6&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I have the same kind of problem with transformers 3.3.1 and a BertModel, but the error is now an inplace operation on torch.cuda.LongTe... | 1,593 | 1,602 | 1,599 | CONTRIBUTOR | null | # 🐛 Bug
## Information
I'm using the pretrained `TransfoXLLMHeadModel` for finetuning but I get an error when trying to use it with pytorch's `DistributedDataParallel`:
> self.reducer.prepare_for_backward(list(_find_tensors(output)))
RuntimeError: Expected to have finished reduction in the prior iteration before... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5313?src=pr&el=h1) Report\n> Merging [#5313](https://codecov.io/gh/huggingface/transformers/pull/5313?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/08c9607c3d025f9f1a0c40e6d124d5d5d446208e&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | Added new cards for the models. | {
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"Wonderful if we can use embeddings of scientific documents in transformers.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"SPECTER is a great work. Is there any plan to have the... | 1,593 | 1,611 | 1,599 | NONE | null | # 🌟 New model addition
SPECTER: Document-level Representation Learning using Citation-informed Transformers
## Model description
[SPECTER](https://arxiv.org/pdf/2004.07180.pdf) by AllenAI is a new method to generate document-level embedding of scientific documents based on pretraining a Transformer language m... | {
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https://api.github.com/repos/huggingface/transformers/issues/5310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5310/comments | https://api.github.com/repos/huggingface/transformers/issues/5310/events | https://github.com/huggingface/transformers/pull/5310 | 646,313,738 | MDExOlB1bGxSZXF1ZXN0NDQwNjI3NjIz | 5,310 | overflowing tokens are now always returned | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5310?src=pr&el=h1) Report\n> Merging [#5310](https://codecov.io/gh/huggingface/transformers/pull/5310?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/79a82cc06aaa68088639bf9bb000752cfd33a8c6&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | MEMBER | null | closes https://github.com/huggingface/transformers/issues/5293
@thomwolf may be superseded by https://github.com/huggingface/transformers/pull/5308/files | {
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https://api.github.com/repos/huggingface/transformers/issues/5309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5309/comments | https://api.github.com/repos/huggingface/transformers/issues/5309/events | https://github.com/huggingface/transformers/issues/5309 | 646,306,908 | MDU6SXNzdWU2NDYzMDY5MDg= | 5,309 | Links out of date under transformers/examples/README.md | {
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## Information
Under the Big Table of Tasks in `transformers/examples/README.md`, the links for summarization and translation are out of date. They should lead to `examples/seq2seq` instead of `examples/summarization` and `examples/translation`. | {
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https://api.github.com/repos/huggingface/transformers/issues/5308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5308/comments | https://api.github.com/repos/huggingface/transformers/issues/5308/events | https://github.com/huggingface/transformers/pull/5308 | 646,300,946 | MDExOlB1bGxSZXF1ZXN0NDQwNjE3MDU5 | 5,308 | [tokenizers] Updates data processors, docstring, examples and model cards to the new API | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5308?src=pr&el=h1) Report\n> Merging [#5308](https://codecov.io/gh/huggingface/transformers/pull/5308?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/135791e8ef12802ceb21a4abbb3a93f7da1bf390&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | MEMBER | null | Updates the data-processors to the new recommended tokenizers' API instead of the old one.
Also update the docstrings, examples, and model-cards which were using the old API.
Supersede #5310
@sshleifer you have a couple of methods only your models use (bart and marian). I'm not sure about the consequences of upd... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5307?src=pr&el=h1) Report\n> Merging [#5307](https://codecov.io/gh/huggingface/transformers/pull/5307?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/88d7f96e33c3f3e541bcdd913f2ff1e50aa18c1b&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5306 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5306/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5306/comments | https://api.github.com/repos/huggingface/transformers/issues/5306/events | https://github.com/huggingface/transformers/pull/5306 | 646,221,381 | MDExOlB1bGxSZXF1ZXN0NDQwNTUxNTU0 | 5,306 | [Generation] fix docs for decoder_input_ids | {
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"Pinging @sshleifer, @sgugger and @LysandreJik for notification.",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5306?src=pr&el=h1) Report\n> Merging [#5306](https://codecov.io/gh/huggingface/transformers/pull/5306?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/com... | 1,593 | 1,593 | 1,593 | MEMBER | null | Fix docs for decoder input ids. | {
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https://api.github.com/repos/huggingface/transformers/issues/5305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5305/comments | https://api.github.com/repos/huggingface/transformers/issues/5305/events | https://github.com/huggingface/transformers/issues/5305 | 646,146,066 | MDU6SXNzdWU2NDYxNDYwNjY= | 5,305 | Does BERT public an embedding file like glove.840B.300d.txt? | {
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"BERT is a fine-tuning based model. As far as I'm aware, there are no 'embedding files' as such. You could generate embedding relevant to your case, by providing the model with words (see documentation) and generate outputs.",
"> BERT is a fine-tuning based model. As far as I'm aware, there are no 'embedding file... | 1,593 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
Hi, I have seen BERT public the pre-training language model like BERT-based-uncased. Does BERT public an embedding file like glove.840B.300d.txt? Many thanks.
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https://api.github.com/repos/huggingface/transformers/issues/5304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5304/comments | https://api.github.com/repos/huggingface/transformers/issues/5304/events | https://github.com/huggingface/transformers/issues/5304 | 646,118,626 | MDU6SXNzdWU2NDYxMTg2MjY= | 5,304 | Bert Abs not using GPU | {
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"This can be resolved by not using the remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization model but the https://huggingface.co/remi/bertabs-finetuned-extractive-abstractive-summarization. With cnndm prefix I would expect it as a gpu version, but the opposite is the case.\r\nChanging the model fixes t... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using: Bert abs (https://github.com/huggingface/transformers/tree/master/examples/seq2seq/bertabs)
-> remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization model
Language I am using the model on: English
The problem arises when using:
* [x] the official examp... | {
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https://api.github.com/repos/huggingface/transformers/issues/5303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5303/comments | https://api.github.com/repos/huggingface/transformers/issues/5303/events | https://github.com/huggingface/transformers/issues/5303 | 646,086,012 | MDU6SXNzdWU2NDYwODYwMTI= | 5,303 | Attempted relative import with no known parent package | {
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"Changing line 15 in run_summarization.py from \r\n`from .utils_summarization import (` to `from utils_summarization import (`\r\nfixed that error",
"@sshleifer - can you take a look here maybe? ",
"I do have a similar error, when I changed from .utils_summarization import ( to from utils_summarization import (... | 1,593 | 1,595 | 1,594 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using: Bertabs (https://github.com/huggingface/transformers/tree/master/examples/seq2seq/bertabs)
Language I am using the model on: English
The problem arises when using:
[x ] the official example scripts: (give details below)
The tasks I am working on is:
* [x] my... | {
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https://api.github.com/repos/huggingface/transformers/issues/5302 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5302/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5302/comments | https://api.github.com/repos/huggingface/transformers/issues/5302/events | https://github.com/huggingface/transformers/pull/5302 | 646,085,438 | MDExOlB1bGxSZXF1ZXN0NDQwNDQxMTc2 | 5,302 | Transformer-XL: Fixed tokenization of brackets, numbers etc. | {
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"Test fail due to the test in `test_tokenization_fast`, but I have not touched that file.\r\nFor me, the problem is in [test_tokenization_fast.py line 45](../tree/master/tests/test_tokenization_fast.py#L45). It works for me if I replace the path `tests/fixtures/...` with `./fixtures/...`\r\n\r\nShould I fix this?",... | 1,593 | 1,596 | 1,596 | CONTRIBUTOR | null | Fixes #5136
As explained in the above issue, this PR fixes the tokenization of the `TransfoXLTokenizer` by using the `sacremoses` library with an extended feature of tokenizing comma-separated and floating point numbers. That way the input text is tokenized the same way as in the WikiText-103 dateset used for pretr... | {
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https://api.github.com/repos/huggingface/transformers/issues/5301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5301/comments | https://api.github.com/repos/huggingface/transformers/issues/5301/events | https://github.com/huggingface/transformers/issues/5301 | 646,080,877 | MDU6SXNzdWU2NDYwODA4Nzc= | 5,301 | Request for inclusion of PEGASUS for text summarization by Google. | {
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"We are currently working on it as far as I know :-) @sshleifer ",
"Duplicate of #4918 , but yes it is WIP!"
] | 1,593 | 1,593 | 1,593 | NONE | null | # 🚀 Feature request
Google has recently released PEGASUS, a new model for text summarization: https://ai.googleblog.com/2020/06/pegasus-state-of-art-model-for.html. I think It would be interesting to have it included in Transformers library. The code and checkpoints are here: https://github.com/google-research/pega... | {
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https://api.github.com/repos/huggingface/transformers/issues/5300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5300/comments | https://api.github.com/repos/huggingface/transformers/issues/5300/events | https://github.com/huggingface/transformers/issues/5300 | 646,027,884 | MDU6SXNzdWU2NDYwMjc4ODQ= | 5,300 | T5ForConditionalGeneration fp16 nan loss | {
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"See #4586."
] | 1,593 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an offici... | {
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https://api.github.com/repos/huggingface/transformers/issues/5299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5299/comments | https://api.github.com/repos/huggingface/transformers/issues/5299/events | https://github.com/huggingface/transformers/issues/5299 | 646,011,892 | MDU6SXNzdWU2NDYwMTE4OTI= | 5,299 | No documentation for MMBT on official docs | {
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"I also cannot figure out how to use this model.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,593 | 1,599 | 1,599 | CONTRIBUTOR | null | I tried finding MMBT on the official documentation: https://huggingface.co/transformers/ but I could not find any references to it, even though there is an implementation for it in the source code.
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https://api.github.com/repos/huggingface/transformers/issues/5298 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5298/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5298/comments | https://api.github.com/repos/huggingface/transformers/issues/5298/events | https://github.com/huggingface/transformers/issues/5298 | 645,996,245 | MDU6SXNzdWU2NDU5OTYyNDU= | 5,298 | The start and end position of BertForQuestionAnswering | {
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"The position is based on the tokens. So this means that if you have a context: \r\n\r\n\"The dog runs in the park.\" and a question \"Who runs in the park?\" and the corresponding tokens (=`tokenizer(\"Who runs in the park?\", \"The dog runs in the park.\",).input_ids`) are \r\n\r\n`[101, 2040, 3216, 1999, 1996, 2... | 1,593 | 1,593 | 1,593 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/5297 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5297/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5297/comments | https://api.github.com/repos/huggingface/transformers/issues/5297/events | https://github.com/huggingface/transformers/issues/5297 | 645,939,677 | MDU6SXNzdWU2NDU5Mzk2Nzc= | 5,297 | Can we have a way for a tokenizer to transform word level or character level annotations? | {
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"I just found out about the `return_offsets_mapping` functionality in the `PreTrainedTokenizerFast` tokenizers. I think I can use that functionality to solve my problem. ",
"@brian8128 could you share a code example of how you do that?",
"Hey Avijit - I didn't test this because it's sort of copied from various ... | 1,593 | 1,594 | 1,593 | NONE | null | # 🚀 Feature request
If I have a string with some annotations and I want to tokenize it I'd like the tokenizer to be able to transform the annotations as well. For example suppose I have `s = "therein lies the problem."` and I'm interested in the substring `"the problem"`. So I have a string `s` and I know that the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5296/comments | https://api.github.com/repos/huggingface/transformers/issues/5296/events | https://github.com/huggingface/transformers/pull/5296 | 645,920,119 | MDExOlB1bGxSZXF1ZXN0NDQwMzE0NDkw | 5,296 | Update outdated TensorFlow -> PyTorch model transfer CLI example | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5296?src=pr&el=h1) Report\n> Merging [#5296](https://codecov.io/gh/huggingface/transformers/pull/5296?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7cc15bdd9675d1cec9186a8963c1f59be899ee68&el=desc) will **decrease... | 1,593 | 1,604 | 1,604 | CONTRIBUTOR | null | The example is outdated and reports an error. | {
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https://api.github.com/repos/huggingface/transformers/issues/5295 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5295/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5295/comments | https://api.github.com/repos/huggingface/transformers/issues/5295/events | https://github.com/huggingface/transformers/issues/5295 | 645,877,261 | MDU6SXNzdWU2NDU4NzcyNjE= | 5,295 | Is summing of attention_mask intended? | {
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"Yes, it's intended. The attention mask has values of 0 where its attending to the tokens, and has a value of `-10000` for tokens it's not attending. By summing this attention mask, it zeros out the attentions that should not be kept. See [here](https://github.com/huggingface/transformers/blob/2ffef0d0c7a6cfa5a59c4... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | # ❓ Questions & Help
Is summing of `attention_mask` intended?
## Details
Documents describe `attention_mask` as a mask to avoid performing attention on padding token indices.
However from the [code](https://github.com/huggingface/transformers/blob/2ffef0d0c7a6cfa5a59c4b883849321f66c79d62/src/transformers/modeling... | {
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https://api.github.com/repos/huggingface/transformers/issues/5294 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5294/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5294/comments | https://api.github.com/repos/huggingface/transformers/issues/5294/events | https://github.com/huggingface/transformers/issues/5294 | 645,837,143 | MDU6SXNzdWU2NDU4MzcxNDM= | 5,294 | Slow Integration Test for examples/seq2seq/finetune.py | {
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"ok cool",
"I will work on this.\r\n\r\n@sshleifer, is it supposed to be w/o a tokenizer?\r\n\r\n```\r\nfrom transformers import AutoTokenizer\r\n\r\ntokenizer = AutoTokenizer.from_pretrained(\"sshleifer/student_xsum_12_3\")\r\n```\r\n\r\n```\r\nOSError: Model name 'sshleifer/student_xsum_12_3' was not found in t... | 1,593 | 1,595 | 1,595 | CONTRIBUTOR | null | Train `sshleifer/student-xsum-12-3` for N batches on xsum data.
Ensure that loss goes down. and is below ~2.
This test should ONLY run on GPU and takes between 30s and 3 mins.
python code to fetch xsum data:
```
import wget
import tarfile
wget.download('https://s3.amazonaws.com/datasets.huggingface.co/... | {
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"Hi! Do you mind pasting the command you use to run the script?",
"I'm facing the same error while training Electra and MiniLM on Squad:\r\nValueError: Input [] is not valid. Should be a string, a list/tuple of strings or a list/tuple of integers.\r\n\r\nThis error is thrown up after reading of about 2% of the ex... | 1,593 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
[*] the official example scripts: (give details below)
[ ] my own modified scripts: (give details below)
The tasks I am working on is:
[*] an... | {
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"I met save issue before. Based on my experience, it is more related to PyTorch. \r\nSee https://pytorch.org/tutorials/beginner/saving_loading_models.html, you should use state_dict to save and load model.",
"But @FacingBugs, this is an issue with the tokenizers and not the models ",
"For tokenizer, using Tran... | 1,593 | 1,599 | 1,599 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Albert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5291?src=pr&el=h1) Report\n> Merging [#5291](https://codecov.io/gh/huggingface/transformers/pull/5291?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/79a82cc06aaa68088639bf9bb000752cfd33a8c6&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | Changes:
- Don't run pytest with `-v` or `--cov`. I left run_tests_torch_and_tf using `--cov` but would love to delete that. I have never used circleci to determine code coverage.
- the run* jobs create artifact files called test_output.txt that are easier to read than scrolling in the circleci gui
- self sche... | {
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"@tqdo There is extensive info and a spreadsheet [here](https://huggingface.co/transformers/benchmarks.html?highlight=benchmark).",
"Thanks a lot"
] | 1,593 | 1,593 | 1,593 | NONE | null | Just curious whether there is any benchmark for inference speed of models in the transformers library? I am interested in the question-answer task but I think a benchmark on any tasks that BERT can do should be good. Thank you. | {
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https://api.github.com/repos/huggingface/transformers/issues/5289 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5289/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5289/comments | https://api.github.com/repos/huggingface/transformers/issues/5289/events | https://github.com/huggingface/transformers/pull/5289 | 645,801,057 | MDExOlB1bGxSZXF1ZXN0NDQwMjE2MTc1 | 5,289 | [pipelines] Change summarization default to distilbart-cnn-12-6 | {
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"CI Failure is spurious.",
"Could you please tell me in **distilbart-cnn-12-6** what does **12 & 6** stands for?",
"12 Encoder layers and 6 decoder layers I would suggest",
"Thank you Sir, @patrickvonplaten "
] | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | - Also adds an integration test that runs on GPU if available.
- Other pipelines could do the same if that would be helpful. | {
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https://api.github.com/repos/huggingface/transformers/issues/5288 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5288/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5288/comments | https://api.github.com/repos/huggingface/transformers/issues/5288/events | https://github.com/huggingface/transformers/issues/5288 | 645,800,009 | MDU6SXNzdWU2NDU4MDAwMDk= | 5,288 | Is there a Longformer For Sequence Classification? | {
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"It is [there](https://github.com/huggingface/transformers/blob/24f46ea3f3e5006ca38735306753a846a0823174/src/transformers/modeling_longformer.py#L796). \r\n\r\nYou may need to use a source install, I'm not sure it was already there in the last release.",
"Thanks. It was in the release but it just wasnt in the doc... | 1,593 | 1,595 | 1,595 | NONE | null | I noticed that Longformer does not have a "LongformerForSequenceClassification". Is there a reason for this and is this something that would be added in the near future? | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5287?src=pr&el=h1) Report\n> Merging [#5287](https://codecov.io/gh/huggingface/transformers/pull/5287?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/24f46ea3f3e5006ca38735306753a846a0823174&el=desc) will **increase... | 1,593 | 1,593 | 1,593 | MEMBER | null | Various improvements for tokenizers:
- Avoid recursion loop for special tokens id look-up in Fast tokenizers
- Fix #5232 by removing the unsupported method `convert_tokens_to_string` for Fast tokenizers
- Fix #5256 by aligning the behavior of the slow tokenizer on the behavior of the fast tokenizer for special token... | {
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https://api.github.com/repos/huggingface/transformers/issues/5286 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5286/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5286/comments | https://api.github.com/repos/huggingface/transformers/issues/5286/events | https://github.com/huggingface/transformers/issues/5286 | 645,775,923 | MDU6SXNzdWU2NDU3NzU5MjM= | 5,286 | save_pretrained on master results in tokenizers that cannot be loaded in v2.11 | {
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"Would it be possible to run \r\n```\r\npip install transformers --upgrade\r\n``` \r\nand try again? We have fixed a lot of bugs since 2.8.0\r\n\r\nPasted tracebacks are much easier to read than screenshots.\r\n",
"I belive that i was runing it. Let me try one more time.\n\nчт, 25 июня 2020 г., 21:50 Sam Shleifer... | 1,593 | 1,595 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using sshleifer/distilbart- *
The problem arises when using:
tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-xsum-12-3") -it fails here
## To reproduce
Steps to reproduce the behavior:
tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-... | {
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https://api.github.com/repos/huggingface/transformers/issues/5285 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5285/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5285/comments | https://api.github.com/repos/huggingface/transformers/issues/5285/events | https://github.com/huggingface/transformers/issues/5285 | 645,765,840 | MDU6SXNzdWU2NDU3NjU4NDA= | 5,285 | Roberta's Positional Embedding Offset | {
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"That's certainly possible. As you can see from my comment, and PR #5188 , I don't fully understand the motivation for the offset. It is very tricky.",
"I figured out why. See here https://github.com/pytorch/fairseq/issues/1177\r\nSo basically the purpose is to make positional embedding = 0 on padding positions (... | 1,593 | 1,604 | 1,604 | NONE | null | https://github.com/huggingface/transformers/blob/d4c2cb402d6674211726fd5f4803d1090664e438/src/transformers/modeling_bart.py#L754
https://github.com/huggingface/transformers/blob/d4c2cb402d6674211726fd5f4803d1090664e438/src/transformers/modeling_bart.py#L763
So this offset is added because the function `create_pos... | {
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https://api.github.com/repos/huggingface/transformers/issues/5284 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5284/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5284/comments | https://api.github.com/repos/huggingface/transformers/issues/5284/events | https://github.com/huggingface/transformers/issues/5284 | 645,753,135 | MDU6SXNzdWU2NDU3NTMxMzU= | 5,284 | Tokenizer batch_encode_plus unexpected behavior | {
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"Yes, this was fixed on master today with https://github.com/huggingface/transformers/pull/5252\r\n"
] | 1,593 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
bert-base-multilingual-cased
Language I am using the model on (English, Chinese ...):
English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
A script ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5283?src=pr&el=h1) Report\n> Merging [#5283](https://codecov.io/gh/huggingface/transformers/pull/5283?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0e1fce3c0129d05b65a83cdd89e8eadded553f2e&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5282 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5282/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5282/comments | https://api.github.com/repos/huggingface/transformers/issues/5282/events | https://github.com/huggingface/transformers/issues/5282 | 645,669,414 | MDU6SXNzdWU2NDU2Njk0MTQ= | 5,282 | Bart: Instatiate lm_head once without wasting memory | {
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"this will happen as part of TPU issue.",
"Can you link the issue? Is there an open PR for this already? ",
"This one: https://github.com/huggingface/transformers/pull/5960 , but it's broken afaict.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed ... | 1,593 | 1,607 | 1,607 | CONTRIBUTOR | null | Marking this down since I agreed to do it https://github.com/huggingface/transformers/pull/4803#discussion_r443381438
cc @patrickvonplaten
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https://api.github.com/repos/huggingface/transformers/issues/5281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5281/comments | https://api.github.com/repos/huggingface/transformers/issues/5281/events | https://github.com/huggingface/transformers/issues/5281 | 645,669,237 | MDU6SXNzdWU2NDU2NjkyMzc= | 5,281 | Segmentation fault when trying to load models | {
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"Bumping to `torch==1.5.1` fixes this issue. But it's still unclear why.",
"I have also met the same issue and upgrading to torch1.5.1 also solves my problem.",
"Possibly related to https://github.com/huggingface/transformers/issues/4857",
"**Downgrade to sentencepiece==0.1.91 solve it.** \r\nI am using PyTo... | 1,593 | 1,676 | 1,596 | NONE | null | We are using `Azure ML` pipelines to train our `transformers` models. We have had it working for a few weeks, and then recently (just noticed it a few days ago), when trying to initialize a model, we are getting `Segmentation fault`.
I tried just loading the models locally this morning and have the same issues. Se... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5280?src=pr&el=h1) Report\n> Merging [#5280](https://codecov.io/gh/huggingface/transformers/pull/5280?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0e1fce3c0129d05b65a83cdd89e8eadded553f2e&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | Now that someone has done an awesome version selector for the docs, there's no need to list all versions in the README. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5279?src=pr&el=h1) Report\n> Merging [#5279](https://codecov.io/gh/huggingface/transformers/pull/5279?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7c41057d5090f5e665f2404878369ecb13939def&el=desc) will **decrease... | 1,593 | 1,600 | 1,594 | MEMBER | null | # Dense Passage Retrieval
## Intro
The Dense Passage Retrieval (DPR) model from facebook ([github](https://github.com/facebookresearch/DPR), [arxiv](https://arxiv.org/abs/2004.04906)).
It is used to do Open Domain Question Answering by extracting answer spans from a set of documents.
This model actually comes i... | {
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```!python transformers-cli convert --model_type xlnet```
I'm getting the following error :
```python: can't open file 'transformers-cli': [Errno 2] No such file or directory```
Any possible fix to this problem? thank you | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5276?src=pr&el=h1) Report\n> Merging [#5276](https://codecov.io/gh/huggingface/transformers/pull/5276?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0e1fce3c0129d05b65a83cdd89e8eadded553f2e&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5275 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5275/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5275/comments | https://api.github.com/repos/huggingface/transformers/issues/5275/events | https://github.com/huggingface/transformers/issues/5275 | 645,614,783 | MDU6SXNzdWU2NDU2MTQ3ODM= | 5,275 | Description of how to preprocess text corpus for roBERTa LM training | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"Well - this issue is still open IMO...",
"This issue has been automatically marked as stale because it has not had recent activity. I... | 1,593 | 1,610 | 1,610 | CONTRIBUTOR | null | # 🚀 Feature request
There are different locations where you desribe how to train roBERTa models. For example here:
- https://huggingface.co/blog/how-to-train
- https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb
- https://gist.github.com/aditya-malte/2d4f896f471b... | {
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https://api.github.com/repos/huggingface/transformers/issues/5273 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5273/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5273/comments | https://api.github.com/repos/huggingface/transformers/issues/5273/events | https://github.com/huggingface/transformers/issues/5273 | 645,595,704 | MDU6SXNzdWU2NDU1OTU3MDQ= | 5,273 | I have some problems with the "bert-large-uncased" model | {
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"Hi, I tried reproducing with the following code, but couldn't get it to crash:\r\n\r\n```py\r\nfrom transformers import BertTokenizer, BertModel, BertConfig\r\n\r\nclass Args:\r\n bert_model = \"bert-large-uncased\"\r\n\r\nargs = Args()\r\n\r\nconfig = BertConfig.from_pretrained(args.bert_model, output_hidden_s... | 1,593 | 1,593 | 1,593 | NONE | null | This is the wrong code segment：
from transformers import BertTokenizer, BertModel, BertConfig
config = BertConfig.from_pretrained(args.bert_model, output_hidden_states = True, output_attentions = True)
tokenizer = BertTokenizer.from_pretrained(args.bert_model, do_lower_case=True, output_hidden_states=True)
bert =... | {
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https://api.github.com/repos/huggingface/transformers/issues/5272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5272/comments | https://api.github.com/repos/huggingface/transformers/issues/5272/events | https://github.com/huggingface/transformers/issues/5272 | 645,536,259 | MDU6SXNzdWU2NDU1MzYyNTk= | 5,272 | A question about the test accuracy of BERT-based-uncased model on the MNLI dataset | {
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"Same, I can't replicate the results in the README file.",
"> Same, I can't replicate the results in the README file.\r\n\r\nI also try to use BERT-large-uncased model and get 0.6209 eval_mnli/acc and 0.6281 eval_mnli-mm/acc.",
"FYI, I can get 84.25 eval_mnli/acc by using a non-zero number of warmup steps. . \r... | 1,593 | 1,599 | 1,599 | NONE | null | # 🐛 Bug
I am curious about how accuracy you guys can reach by using the BERT-based-uncased model on the MNLI task? I got 61% test accuracy on the MNLI-matched dataset and 62% accuracy on the MNLI-unmatched dataset.
## Information
Model I am using Bert-based-uncased:
Language I am using the model on English:
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5271/comments | https://api.github.com/repos/huggingface/transformers/issues/5271/events | https://github.com/huggingface/transformers/issues/5271 | 645,502,947 | MDU6SXNzdWU2NDU1MDI5NDc= | 5,271 | BART finetune.py: model not learning anything | {
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"Seems to be coming from the --warmup_steps arg. If I set to 0, the model seems to learn as expected. If it is > 0 the model doesn't learn anything.",
"Interesting. Could you link me to that dataset/instructions?\r\nI just reran cnn_dm with warmup_steps=0 and my loss curve looks very similar in wandb. pink is no ... | 1,593 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [x] the official example scripts: (give details below)
./examples/summarization/finetune.sh
* [ ] my own modified scripts: (give details below)
The task... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5270?src=pr&el=h1) Report\n> Merging [#5270](https://codecov.io/gh/huggingface/transformers/pull/5270?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0e1fce3c0129d05b65a83cdd89e8eadded553f2e&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | Create README.md for finance-koelectra-base-discriminator model | {
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https://api.github.com/repos/huggingface/transformers/issues/5269 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5269/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5269/comments | https://api.github.com/repos/huggingface/transformers/issues/5269/events | https://github.com/huggingface/transformers/pull/5269 | 645,396,193 | MDExOlB1bGxSZXF1ZXN0NDM5ODgzNjQ0 | 5,269 | Fix LR decay in TF Trainer | {
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"@LysandreJik Sorry for the inconvenience :(",
"Will merge once the code quality passes",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5269?src=pr&el=h1) Report\n> Merging [#5269](https://codecov.io/gh/huggingface/transformers/pull/5269?src=pr&el=desc) into [master](https://codecov.io/gh/hug... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | Revival of #5051
I have accidentally deleted the previous branch so I recreated this same one. | {
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https://api.github.com/repos/huggingface/transformers/issues/5268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5268/comments | https://api.github.com/repos/huggingface/transformers/issues/5268/events | https://github.com/huggingface/transformers/pull/5268 | 645,377,215 | MDExOlB1bGxSZXF1ZXN0NDM5ODY2Mzg4 | 5,268 | Fix LR decay in TF Trainer | {
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I have accidentally deleted the previous branch so I recreated this same one. | {
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https://api.github.com/repos/huggingface/transformers/issues/5267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5267/comments | https://api.github.com/repos/huggingface/transformers/issues/5267/events | https://github.com/huggingface/transformers/issues/5267 | 645,150,768 | MDU6SXNzdWU2NDUxNTA3Njg= | 5,267 | ValueError in T5 community colab notebook. | {
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"hi @y-rokutan, you are right, `DataCollator` is not a `Class` anymore, its a `callable` now, so remove subclassing and change `collate_batch` method to ` __call__` \r\n\r\nI'll update the notebook once new version of transformers is released",
"hi @patil-suraj, thx for your quick reply. I appreciate your contr... | 1,593 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): T5
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the community notebook https://github.com/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb:
* It raises subclassing error while definin... | {
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https://api.github.com/repos/huggingface/transformers/issues/5266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5266/comments | https://api.github.com/repos/huggingface/transformers/issues/5266/events | https://github.com/huggingface/transformers/issues/5266 | 645,145,563 | MDU6SXNzdWU2NDUxNDU1NjM= | 5,266 | Finetune T5 on other Dataset, AssertionError: assert tokenized.input_ids.shape[1] == max_length | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,593 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
## Details
I was trying to finetune Amazon Food Review Dataset on T5 using **Latest code from master**.
I formatted the data, as .source and .target.
When running [finetune_t5.sh](https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune.py),
First it gives error... | {
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https://api.github.com/repos/huggingface/transformers/issues/5265 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5265/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5265/comments | https://api.github.com/repos/huggingface/transformers/issues/5265/events | https://github.com/huggingface/transformers/issues/5265 | 645,121,297 | MDU6SXNzdWU2NDUxMjEyOTc= | 5,265 | test_torch_fillmask failing on GPU | {
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"note to self: enro also fails on cpu, and rerunning on commit where it was green now fails. So change is something S3 related.\r\n",
"```python\r\ntests/test_pipelines.py:148: in _test_mono_column_pipeline\r\n set([o[key] for o in result]), set([o[key] for o in expect]),\r\nE AssertionError: Items in the fi... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | ```bash
FAILED tests/test_modeling_bart.py::MBartIntegrationTests::test_enro_forward
expected_slice = torch.tensor([9.0078, 10.1113, 14.4787], device=torch_device, dtype=model.dtype)
result_slice = logits[0][0][:3]
> self.assertTrue(torch.allclose(expected_slice, result_slice, atol=TOLERANCE... | {
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https://api.github.com/repos/huggingface/transformers/issues/5264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5264/comments | https://api.github.com/repos/huggingface/transformers/issues/5264/events | https://github.com/huggingface/transformers/issues/5264 | 645,097,325 | MDU6SXNzdWU2NDUwOTczMjU= | 5,264 | Set the number of times to evaluate per epoch when using Trainer | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,593 | 1,598 | 1,598 | CONTRIBUTOR | null | Basically, I want to see how the training is going against the evaluation dataset twice per epoch when using `Trainer`. To calculate `logging_steps` so that `evaluate()` is called a certain number of times per epoch when training, will this hold-up to single and multi-device training?
```
evals_per_epoch = 2
loggi... | {
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https://api.github.com/repos/huggingface/transformers/issues/5263 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5263/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5263/comments | https://api.github.com/repos/huggingface/transformers/issues/5263/events | https://github.com/huggingface/transformers/issues/5263 | 645,079,591 | MDU6SXNzdWU2NDUwNzk1OTE= | 5,263 | [examples] Verify marian and mbart BLEU scores with examples/seq2seq/run_eval.py | {
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"Surprised. Maybe the opus data overlaps the wmt test set?",
"\r\n",
"Opus #s are legit!",
"@sshleifer do you using the default configuration in Readme ? I didn't get 37.1, and I have tried the configu... | 1,593 | 1,602 | 1,602 | CONTRIBUTOR | null | Got MBART 26.8 before postprocessing on wmt_en_ro, 37.1 after.
6 minutes. (first # same as fairseq, second should be also).
Marian: 27.7/37.4 90 Seconds | {
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https://api.github.com/repos/huggingface/transformers/issues/5262 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5262/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5262/comments | https://api.github.com/repos/huggingface/transformers/issues/5262/events | https://github.com/huggingface/transformers/issues/5262 | 645,078,924 | MDU6SXNzdWU2NDUwNzg5MjQ= | 5,262 | Cannot control wandb metadata when running examples/seq2seq/finetune.py | {
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"You should be able to do it with environment variables. See [these docs](https://docs.wandb.com/library/environment-variables)\r\nLet me know if that solves the issue.\r\n\r\nThe reason of the current implementation (and auto init of wandb) was to be able to instrument all example scripts without having to add cus... | 1,593 | 1,594 | 1,594 | CONTRIBUTOR | null | There is no easy way to control the wandb project_name kwarg.
How can we facilitate this without massive number of command line args?
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https://api.github.com/repos/huggingface/transformers/issues/5261 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5261/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5261/comments | https://api.github.com/repos/huggingface/transformers/issues/5261/events | https://github.com/huggingface/transformers/issues/5261 | 645,073,457 | MDU6SXNzdWU2NDUwNzM0NTc= | 5,261 | [proposal] Move tests/utils.py to src/transformers/testing_utils.py so that examples can import | {
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"I think that would be cool. Since we're testing the examples, it makes sense to not duplicate the exact same code.",
"Sounds good to me"
] | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null |
for both groups of tests, the import would be
```python
from transformers.testing_utils import slow
```
Motivation: I was about to rewrite the @slow decorator today and felt that this was cleaner.
Any objections? @julien-c @LysandreJik @thomwolf @sgugger @patrickvonplaten @mfuntowicz
@anyoneelseimforgettin... | {
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https://api.github.com/repos/huggingface/transformers/issues/5260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5260/comments | https://api.github.com/repos/huggingface/transformers/issues/5260/events | https://github.com/huggingface/transformers/issues/5260 | 645,059,403 | MDU6SXNzdWU2NDUwNTk0MDM= | 5,260 | BertTokenizerFast does not support `pad_to_max_length` argument | {
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"Hi @jarednielsen, if you installed from source then padding is handled in a different way. You'll need to use the newly added `padding` argument. According to the docs \r\n\r\n`padding` (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`False`):\r\n Activate and control padding. Accepts the followi... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
The fast tokenizer has different behavior from the normal tokenizer.
```python
from transformers import BertTokenizer, BertTokenizerFast
BertTokenizer.from_pretrained("bert-base-uncased").encode("hello world", max_length=128, pad_to_max_length="right")
# succeeds
BertTokenizerFast.from_pretrained("... | {
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https://api.github.com/repos/huggingface/transformers/issues/5259 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5259/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5259/comments | https://api.github.com/repos/huggingface/transformers/issues/5259/events | https://github.com/huggingface/transformers/pull/5259 | 645,044,647 | MDExOlB1bGxSZXF1ZXN0NDM5NTczOTk0 | 5,259 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5259?src=pr&el=h1) Report\n> Merging [#5259](https://codecov.io/gh/huggingface/transformers/pull/5259?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d12ceb48bad126768e44d2bd958fa7638abd0f16&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/5258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5258/comments | https://api.github.com/repos/huggingface/transformers/issues/5258/events | https://github.com/huggingface/transformers/pull/5258 | 645,015,286 | MDExOlB1bGxSZXF1ZXN0NDM5NTQ5Nzkx | 5,258 | save_pretrained: mkdir(exist_ok=True) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5258?src=pr&el=h1) Report\n> Merging [#5258](https://codecov.io/gh/huggingface/transformers/pull/5258?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/efae6645e223f29cf05eeafe95105a9f869b66dd&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | CONTRIBUTOR | null | Old Logic:
if you pass something that is not a pre-existing directory -> Error
New Logic:
if you pass a file that exists -> Error.
if you pass a path that doesn't exist -> we call `mkdir path`, no error.
if you pass an existing directory -> no error.
This is not a breaking change, since no calls that previous... | {
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https://api.github.com/repos/huggingface/transformers/issues/5257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5257/comments | https://api.github.com/repos/huggingface/transformers/issues/5257/events | https://github.com/huggingface/transformers/pull/5257 | 644,982,096 | MDExOlB1bGxSZXF1ZXN0NDM5NTIxNjY2 | 5,257 | Tokenization tutorial | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5257?src=pr&el=h1) Report\n> Merging [#5257](https://codecov.io/gh/huggingface/transformers/pull/5257?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0148c262e79f5ca12140d7fc35a6d3e0d80d5d3b&el=desc) will **decrease... | 1,593 | 1,593 | 1,593 | COLLABORATOR | null | This takes most of the description in #4510 and organizes it as a tokenizer tutorial for section 2 of the documentation.
Preview is [here](https://52645-155220641-gh.circle-artifacts.com/0/docs/_build/html/preprocessing.html). | {
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https://api.github.com/repos/huggingface/transformers/issues/5256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5256/comments | https://api.github.com/repos/huggingface/transformers/issues/5256/events | https://github.com/huggingface/transformers/issues/5256 | 644,956,043 | MDU6SXNzdWU2NDQ5NTYwNDM= | 5,256 | RobertaTokenizerFast produces a different output than RobertaTokenizer | {
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"For records for the new users: Now, it seemed to have been resolved. I tried to reproduce this in my notebook but getting same results for both of them:\r\n\r\n<img width=\"1383\" alt=\"image\" src=\"https://github.com/huggingface/transformers/assets/104596164/bde951ac-8b9c-4996-966b-1d11f4c12d35\">\r\n"
] | 1,593 | 1,684 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
`RobertaTokenizerFast.tokenize()` produces a different output than `RobertaTokenizer.tokenize()`. I am not sure if this is an issue that will impact model performance. Is this intended? I assumed the fast tokenizers should be consistent with the normal ones in terms of outputs.
## Information
Model I ... | {
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https://api.github.com/repos/huggingface/transformers/issues/5255 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5255/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5255/comments | https://api.github.com/repos/huggingface/transformers/issues/5255/events | https://github.com/huggingface/transformers/pull/5255 | 644,860,276 | MDExOlB1bGxSZXF1ZXN0NDM5NDExMzAy | 5,255 | Fix first test | {
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https://api.github.com/repos/huggingface/transformers/issues/5254 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5254/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5254/comments | https://api.github.com/repos/huggingface/transformers/issues/5254/events | https://github.com/huggingface/transformers/pull/5254 | 644,856,787 | MDExOlB1bGxSZXF1ZXN0NDM5NDA4MTY2 | 5,254 | Move GenerationMixin to separate file | {
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Both of these files were getting pretty long, with the code dedicated to generation taking about 1000 LOC in each while bein... | {
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This PR adds more tests to cover various combinations of padding + truncation strategies.
Fix #5181
T... | {
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In particular:
- not sure that `location.toString()` will end with a '/' or not when on the index, this works with both
- when nested, use the previous value and not an absolute one
- the base url needs to be slice up to the versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/5250 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5250/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5250/comments | https://api.github.com/repos/huggingface/transformers/issues/5250/events | https://github.com/huggingface/transformers/pull/5250 | 644,727,873 | MDExOlB1bGxSZXF1ZXN0NDM5Mjk5NjMw | 5,250 | Fix tensor label type inference in default collator | {
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"What's the perf impact of a try/catch?",
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"Dug a bit deeper. It seems encode doesn't deterministically tokenize on white-spaces. In the cat example: 16101 -> \"super\" and 2422 -> \" super\". Is there an option in encode to force white space splitting. I guess the hack is to tokenize each word separately but that rather inefficient ",
"For the GPT2/Robe... | 1,593 | 1,593 | 1,593 | NONE | null | I working on a sequence tagging task where I to extract cause and effect sub spans for a given text. For example, extract <e1> and <e2> for the text below.
`"<e2>The Sunshine State drew in a net influx of about $17.7 billion in adjusted gross income (AGI) - most of which (72 percent) came from those aged 55 and ol... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5247?src=pr&el=h1) Report\n> Merging [#5247](https://codecov.io/gh/huggingface/transformers/pull/5247?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/aa6a29bc25b663e1311c5c4fb96b004cf8a6d2b6&el=desc) will **increase... | 1,593 | 1,603 | 1,603 | CONTRIBUTOR | null | By default there is no implementation of cross entropy with soft labels in Pytorch as discussed in #5168
I found a feature request in pytorch for it but it is still not done.
https://github.com/pytorch/pytorch/issues/7455
There is also discussion where i found an implemented version of this loss. I checked th... | {
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1) - The default model class to benchmark is the one that can be found under config.architectures
2) - Improve plotting file | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5240?src=pr&el=h1) Report\n> Merging [#5240](https://codecov.io/gh/huggingface/transformers/pull/5240?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7c41057d5090f5e665f2404878369ecb13939def&el=desc) will **decrease... | 1,593 | 1,651 | 1,599 | MEMBER | null | This PR superseded #4864
This PR examines how to best make use of all the features of 🤗nlp in the examples.
First example studied is GLUE. The main goal is to have explicit data processing (target: no data processing happening inside transformers) as well as add some efficiency features like dynamic/optimized b... | {
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https://api.github.com/repos/huggingface/transformers/issues/5239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5239/comments | https://api.github.com/repos/huggingface/transformers/issues/5239/events | https://github.com/huggingface/transformers/issues/5239 | 644,566,742 | MDU6SXNzdWU2NDQ1NjY3NDI= | 5,239 | Multilingual MNLI model | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,593 | 1,598 | 1,598 | NONE | null | Hi,
I'm trying Zero-Shot Learning with 'facebook/bart-large-mnli' and it's pretty well, but I want to do it in Spanish. Is there any multilingual mnli model?
Thanks for your attention! | {
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https://api.github.com/repos/huggingface/transformers/issues/5238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5238/comments | https://api.github.com/repos/huggingface/transformers/issues/5238/events | https://github.com/huggingface/transformers/issues/5238 | 644,565,283 | MDU6SXNzdWU2NDQ1NjUyODM= | 5,238 | Not Implemented Error | {
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"This is likely due because you are using a wrong version of Tensorflow. Can you run `transformers-cli env`, as the template suggests, and place the result here?",
"Can you post the full stack trace? It's hard to debug this way.",
"@BramVanroy for your reference\r\n\r\n```\r\n-----------------------------------... | 1,593 | 1,676 | 1,600 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): TFBert
Language I am using the model on (English, Chinese ...): Any
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
## To reproduce
I am trying to ru... | {
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https://api.github.com/repos/huggingface/transformers/issues/5237 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5237/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5237/comments | https://api.github.com/repos/huggingface/transformers/issues/5237/events | https://github.com/huggingface/transformers/issues/5237 | 644,476,456 | MDU6SXNzdWU2NDQ0NzY0NTY= | 5,237 | BART(base) - Finetune Is this a bug ? Or I am doing something wrong? | {
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"Can you post the full error message?",
"Are you asking for this or more??\r\n```bash\r\nTypeError Traceback (most recent call last)\r\n\r\n<ipython-input-13-31ed8b67b601> in <module>()\r\n 2 # see ``examples/summarization/bart/run_eval.py`` for a longer example\r\n 3 mod... | 1,592 | 1,592 | 1,592 | NONE | null | ## I have finetuned my dataset using latest piece of code from master, by cloning and the building.
Now when I try to load my finetuned model as shown in the examples of "summarization" (previous commit).
`from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
model = BartForConditiona... | {
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https://api.github.com/repos/huggingface/transformers/issues/5236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5236/comments | https://api.github.com/repos/huggingface/transformers/issues/5236/events | https://github.com/huggingface/transformers/pull/5236 | 644,467,159 | MDExOlB1bGxSZXF1ZXN0NDM5MDgzNDQ3 | 5,236 | Model cards for Hate-speech-CNERG models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5236?src=pr&el=h1) Report\n> Merging [#5236](https://codecov.io/gh/huggingface/transformers/pull/5236?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5e31a98ab70607c820cc2ad358d81916adad0313&el=desc) will **decrease... | 1,592 | 1,593 | 1,593 | CONTRIBUTOR | null | Made minor updates in previous model cards and added new cards for the newly updated models. | {
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https://api.github.com/repos/huggingface/transformers/issues/5235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5235/comments | https://api.github.com/repos/huggingface/transformers/issues/5235/events | https://github.com/huggingface/transformers/issues/5235 | 644,440,362 | MDU6SXNzdWU2NDQ0NDAzNjI= | 5,235 | Does to T5 Transformer training scale to multiple GPUs? | {
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"Hi @abhisheknovoic , you can use T5 on multiple GPU's. Have a look at this community notebook https://github.com/patil-suraj/exploring-T5/blob/master/t5_fine_tuning.ipynb.\r\n\r\nIt uses pytorch-lightning, so its very easy to setup multi-gpu training.See this guide https://pytorch-lightning.readthedocs.io/en/lates... | 1,592 | 1,604 | 1,598 | NONE | null | Hello team,
I have a large set of sequence to sequence dataset. Basically, a huge bunch of input text sequences to output text sequences. I want to train a T5 network on this. I have the following specific questions.
a. Can I use the sample code here (along with my own code) to train T5 on my data? - https://hu... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
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https://api.github.com/repos/huggingface/transformers/issues/5233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5233/comments | https://api.github.com/repos/huggingface/transformers/issues/5233/events | https://github.com/huggingface/transformers/pull/5233 | 644,357,788 | MDExOlB1bGxSZXF1ZXN0NDM4OTkzODMz | 5,233 | Fix PABEE division by zero error | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5233?src=pr&el=h1) Report\n> Merging [#5233](https://codecov.io/gh/huggingface/transformers/pull/5233?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9022ef021a56db975d25c7108cbd19d0dd399174&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Fix the `division_by_zero` error when `patience` is set to `0` during inference.
https://github.com/JetRunner/PABEE/issues/2 | {
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https://api.github.com/repos/huggingface/transformers/issues/5232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5232/comments | https://api.github.com/repos/huggingface/transformers/issues/5232/events | https://github.com/huggingface/transformers/issues/5232 | 644,316,548 | MDU6SXNzdWU2NDQzMTY1NDg= | 5,232 | BertTokenizerFast.convert_tokens_to_string converts ids to string, not tokens to string | {
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"You're right, this method is actually not provided on the Fast tokenizers and wrongly linked to the `decode()` method.\r\nWe should remove it in the short-term.\r\n\r\nDo you need it for a specific workflow?",
"I need to decode a sequence of input ids to a string. However, I cannot use `tokenizer.batch_decode` b... | 1,592 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
The `BertTokenizerFast.convert_tokens_to_string` function expects a list of integers instead of a list of strings as the function implies. This does not happen for the normal `BertTokenizer`.
The [BertTokenizerFast](https://github.com/huggingface/transformers/blob/master/src/transformers/tokenization_ber... | {
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https://api.github.com/repos/huggingface/transformers/issues/5231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5231/comments | https://api.github.com/repos/huggingface/transformers/issues/5231/events | https://github.com/huggingface/transformers/issues/5231 | 644,305,954 | MDU6SXNzdWU2NDQzMDU5NTQ= | 5,231 | BertAbs run_summarization.py example fails with errors | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
Attempting to use BertAbs with the official example script for summarization: https://github.com/huggingface/transformers/tree/master/examples/summarization/bertabs#summarize-any-text
The language I am attempting to summarize for is English.
Simply attempting to run a command like
... | {
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https://api.github.com/repos/huggingface/transformers/issues/5230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5230/comments | https://api.github.com/repos/huggingface/transformers/issues/5230/events | https://github.com/huggingface/transformers/pull/5230 | 644,232,095 | MDExOlB1bGxSZXF1ZXN0NDM4ODkxODc0 | 5,230 | Fix convert_graph_to_onnx script | {
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- Check that the wanted framework is installed before creating the pipeline, otherwise, it might fail to instantiate it. | {
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https://api.github.com/repos/huggingface/transformers/issues/5229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5229/comments | https://api.github.com/repos/huggingface/transformers/issues/5229/events | https://github.com/huggingface/transformers/pull/5229 | 644,230,145 | MDExOlB1bGxSZXF1ZXN0NDM4ODkwMzA1 | 5,229 | Cleaning TensorFlow models | {
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"Thanks @LysandreJik !\r\n\r\n> The loss is computed differently than it is with the PyTorch models. Here it is returned example-wise (therefore with a shape of (batch_size,), whereas the PyTorch models return the loss as a scalar. @jplu is there a reason for this implementation?\r\n\r\nBecause it is the generic ap... | 1,592 | 1,593 | 1,593 | MEMBER | null | While writing docstrings for #5036, I stumbled upon a few bugs in TensorFlow, especially related to the loss computation. I'm patching them in this PR.
Here's the list of the bugs solved:
### Loss computation
- The loss is computed differently than it is with the PyTorch models. Here it is returned example-wis... | {
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"Hi,\r\nCan you share a self-contained code example reproducing the bug?",
"> Hi,\r\n> Can you share a self-contained code example reproducing the bug?\r\n\r\nSorry, I think it is due to a bug in my code. Please close it.",
"@zht1130 Were you able to identify the bug? I'm seeing a similar error.",
"> @zht1130... | 1,592 | 1,593 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert cased (size=768)
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below) When I feed the id... | {
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The default version...
1) doesn't call `lr_scheduler.step()`
2) does call `self.trainer.scaler.step(optimizer)`
I haven't diagnosed which of these is the main culprit of the issue I was seeing (very high loss, not going down). This fixes that issue.
I susp... | {
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"I agree with this change but what about backward compat? I think, as you said, `namedtuple` could be used.",
"I think the `namedtuple` would be best for both getting the desired features and also backward compatibility. But to make it backward compatible, wouldn't we just need any object that supports indexing (... | 1,592 | 1,594 | 1,594 | NONE | null | I propose a replacing the default Tuple outputs with payloads where every field in the tuple is accessible by a name. This has the following benefits:
1. Being more accessible to newcomers of the library
2. Eliminating suspicious comments in the source code describing the output (see below)
3. Make it easier to ex... | {
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https://api.github.com/repos/huggingface/transformers/issues/5225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5225/comments | https://api.github.com/repos/huggingface/transformers/issues/5225/events | https://github.com/huggingface/transformers/pull/5225 | 644,085,865 | MDExOlB1bGxSZXF1ZXN0NDM4NzcwODg2 | 5,225 | Add hugs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5225?src=pr&el=h1) Report\n> Merging [#5225](https://codecov.io/gh/huggingface/transformers/pull/5225?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c01480bba3b2f0bd8516679476235f4701c21b3b&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Enforce that there are not transformers, Transformers, `transformers` but only 🤗 Transformers in the documentation. | {
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https://api.github.com/repos/huggingface/transformers/issues/5224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5224/comments | https://api.github.com/repos/huggingface/transformers/issues/5224/events | https://github.com/huggingface/transformers/pull/5224 | 644,061,192 | MDExOlB1bGxSZXF1ZXN0NDM4NzUwMzk3 | 5,224 | Use the script in utils | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5224?src=pr&el=h1) Report\n> Merging [#5224](https://codecov.io/gh/huggingface/transformers/pull/5224?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c01480bba3b2f0bd8516679476235f4701c21b3b&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Since we have the script `download_glue_data` in the utils folder, changing the instructions in the README for the GLUE example to use it for now (of course nlp will ultimately make this even easier) since it's easier than copying the gist in a local file. | {
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https://api.github.com/repos/huggingface/transformers/issues/5223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5223/comments | https://api.github.com/repos/huggingface/transformers/issues/5223/events | https://github.com/huggingface/transformers/pull/5223 | 644,054,568 | MDExOlB1bGxSZXF1ZXN0NDM4NzQ0ODc1 | 5,223 | Only put tensors on a device | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5223?src=pr&el=h1) Report\n> Merging [#5223](https://codecov.io/gh/huggingface/transformers/pull/5223?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c01480bba3b2f0bd8516679476235f4701c21b3b&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | Fix Trainer when users have inputs containing non-tensor values. | {
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https://api.github.com/repos/huggingface/transformers/issues/5222 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5222/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5222/comments | https://api.github.com/repos/huggingface/transformers/issues/5222/events | https://github.com/huggingface/transformers/pull/5222 | 644,045,339 | MDExOlB1bGxSZXF1ZXN0NDM4NzM3Mzc5 | 5,222 | Add version control menu | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5222?src=pr&el=h1) Report\n> Merging [#5222](https://codecov.io/gh/huggingface/transformers/pull/5222?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c439752482759c94784e11a87dcbf08ce69dccf3&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | This PR adds at the top of the navigation bar a menu to pick a version of the docs.
A few comments:
When switching version, the reader is sent on the same page of the docs in the older version (so it gives an error if the same page did not exist in this version of the docs). I don't know if this is preferable to ... | {
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"This may be an error on my part, apologies. Just confirming.",
"This is supposed to work, misaligned address is usually a flavor of OOM. I would try to cut your batch size.",
"@sshleifer Batch size is 16, am on a V100 on FP16. Also I'm training with a batch size of 512, so surely batch size is fine in this cas... | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2
Language I am using the model on (English, Chinese ...): Molecule
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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